code: def load_tacotron(
      tacotron_model_path, code_dict_path, max_decoder_steps
  ):
      ckpt_dict = torch.load(
          tacotron_model_path, map_location=torch.device("cpu")
      )
      hparams = ckpt_dict["hparams"]
      hparams.code_dict = code_dict_path
      hparams.max_decoder_steps = max_decoder_steps
      sr = hparams.sampling_rate
      model = Tacotron2(hparams)
      model.load_state_dict(ckpt_dict["model_dict"])
      model = model.half()
      model = model.eval()
      return model, sr, hparams
  
file_path: textlesslib/textless/vocoders/tacotron2/vocoder.py
imports: import torch.nn
  import torch
  from .tts_data import TacotronInputDataset
  from .model import Tacotron2
  from .glow import WaveGlow
  from .waveglow_denoiser import Denoiser
  from textless.checkpoint_manager import CHECKPOINT_MANAGER
  from typing import Union
label_desc: Use image node_id 2 for calling a global function with example usage: load_tacotron(tacotron_model_path, code_dict_path, max_decoder_steps) and returns: model,  sr,  hparams